Abstract
Maintenance management is a subject that, instead of reducing importance with the increase of equipment reliability, it increases its role in the companies and obliges the increase of the level of demand of professionals involved because of the new technical and environmental demands. Sometimes, scientific developments anticipate the company's needs while other times it is the company that challenges science. The maintenance area is an example that offers challenges to both science and companies in order to optimize the performance of equipment and facilities. However, if during the industrial era the maintenance had to respond to industry, nowadays, and in parallel with the increase of equipment performance, the maintenance has the obligation to aid in order to convert technology in becoming more environmentally friendly. It is because of this kind of challenge that the authors are developing new methodologies, almost antagonistic, because of the areas in development, namely diesel engines and wind generators, and as we will demonstrate, areas which are compatible and can contribute to a better environment. In the case of wind generators, the methodology aims to optimize the cycles of production and consequently, reduce the other kinds of energy production. On the other hand, the methodologies for maintenance of diesel engines are based on environmental indicators that can predict the "health state" taking into account restrictions including health human factors among others. The new methodologies will later be incorporated through new predictive maintenance modules in an integrated maintenance management system called SMIT (Terology Integrated Modular System). The SMIT system includes the main modules of a traditional system, as well as a fault diagnosis. a non-periodic maintenance planning and a generic on-condition maintenance module, among other innovations. The new features will include, in the case of wind generators, on-line measures and the corresponding on-time treatment, using algorithms based on time-series forecasting and wireless technology to transmit the signals. In the case of diesel engines, the algorithms are based on Markov chains and hidden Markov chains, with an approach that is offering good results, which proves the validity of the methodology and the innovation itself. It is based on these developments and the new researches mentioned so far that this paper is built upon, and we believe will be a contribution to the maintenance management area.

Abstract
In the restructured electricity industry, meaningful loss allocation methods are required in order to send correct signals to the market taking into account the location and characteristics of loads and generations, including the local sources forming the distributed generation (DG). This paper addresses the issues related to loss allocation in radial distribution systems with DG, with a three-fold focus. First, the key differences in the formulation of the loss allocation problem for radial distribution systems with respect to transmission systems are discussed, specifying the modeling and computational issues concerning the treatment of the slack node in radial distribution systems. Then, the characteristics of derivative-based and circuit-based loss allocation techniques are presented and compared, illustrating the arrangements used for adapting the various techniques to be applied to radial distribution systems with DG. Finally, the effects of introducing voltage-controllable local generation on the calculation of the loss allocation coefficients are discussed, proposing the adoption of a "reduced" representation of the system capable of taking into proper account the characteristics of the nodes containing voltage-controllable DG units. Numerical results are provided to show the time evolution of the loss allocation coefficients for distribution systems with variable load and local generation patterns.

Abstract
In this paper, the concepts related to loss partitioning among the phase currents in three-phase distribution systems are revisited in the light of new findings identified by the authors. In particular, the presence of a paradox in the classical loss partitioning approach, based on the use of the phase-by-phase difference between the input and output complex power, is highlighted. The conditions for performing effective loss partitioning without the occurrence of the paradox are thus established. The corresponding results are then used to extend the branch current decomposition loss allocation method for enabling its application to three-phase unbalanced distribution systems with distributed generation. Several numerical examples on a three-phase line with grounded neutral and on the modified IEEE 13-node test system are provided to assist the illustration and discussion of the novel conceptual framework. © 2008 IEEE.

Abstract
Nowadays the education on electrical engineering, in European countries, is facing on one side a high demand for engineers coming from industry and on the other hand a reduced interest from younger generation, whose interest is highly polarised by information and communication technologies. A permanent-magnet synchronous motor (PMSM) controller for an electric wheelchair demo track has been set up, in order to reinforce the demonstrative aspects of modern technology as a contribution to the motivation of students for the industrial electronics world. The motors are controlled at different operating conditions by means of a current control law using a low cost microcontroller board. The prototype has been designed specifically to meet the requirement of low cost and it contains all of the active functions required to implement the control of the electric wheelchair. The resulting prototype has a very low cost compared to commercial "black-box" modules. This prototype allows a first approach between a real technical system and power electronics, increasing the student's motivation for the power electronics area and to significantly enhance their skills to measure and interpret measurements and comparing those to theoretical predictions.

Abstract
Battery-powered electric vehicle appear to be one of the viable solutions for the growing concerns for environmental protection and the fast rate of depletion of world fuel oil supply. This type of vehicle can become a viable alternative to the internal combustion engine only if they are able to meet certain reliability, safety, performance, and cost criteria. In addition, this type of electrical vehicles have serious disadvantages because of the limitation on cruising range imposed by weight, capacity of the electric accumulators and long recharging time. Improvement of efficiency of induction motor traction drives is an important issue in pure electric vehicles to improve the running distance on one charge. In this paper, the authors evaluate a loss-minimization algorithm (LMA) by considering their influence on the performance of the vehicle. The evaluation of the proposed LMA is demonstrated experimentally under different operating conditions of the vehicle.

Abstract
Short-term risk management is highly dependent on long-term contractual decisions previously established; risk aversion factor of the agent and short-term price forecast accuracy. Trying to give answers to that problem, this paper provides a different approach for short-term risk management on electricity markets. Based on long-term contractual decisions and making use of a price range forecast method developed by the authors, the short-term risk management tool presented here has as main concern to find the optimal spot market strategies that a producer should have for a specific day in function of his risk aversion factor, with the objective to maximize the profits and simultaneously to practice the hedge against price market volatility. Due to the complexity of the optimization problem, the authors make use of Particle Swarm Optimization (PSO) to find the optimal solution. Results from realistic data, namely from OMEL electricity market, are presented and discussed in detail.